Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study
BMJ 2023; 383 doi: https://doi.org/10.1136/bmj-2023-076990 (Published 22 November 2023) Cite this as: BMJ 2023;383:e076990Linked Editorial
Does timely vaccination help prevent post-viral conditions?
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Dear Editor
Conclusions about vaccine effectiveness against post-Covid 19 condition are not supported by the data
We agree with the responses by Chen and Lacout et al. and want to raise additional serious concerns regarding the conclusions of the study of Lundberg-Morris et al (1).
Firstly, however, we want to underscore the main result of the study: PCC is not as common as initially claimed. The German Minister of Health, for example, maintained that this phenomenon is about six times more frequent. On the other hand, register-based studies are generally error-prone regarding the phenomenon of PCC (2).
In conjunction with the COVID-19 vaccine trials, the debate about relative and absolute risk reduction to describe vaccine effectiveness (VE) has re-emerged (3,4). The relative metric tends to exaggerate results (5), and presentation of only relative data without absolute efficiency is a well-known marketing technique (6-8). It is therefore necessary to include both measures to support evidence-based decisions (9-11). In this study (1), the absolute risk reduction is only 1%, casting serious doubt on the "strong association" that the authors derive from their reported VE of 58% with any number of doses before infection.
The authors stated that 56,760 vaccinated persons and 2515 deceased individuals were excluded because they were vaccinated or died within 28 days of COVID-19 infection. It would be extremely important to know the further course of this vaccinated group and the exact vaccination status of the deceased. This is not reported anywhere. The authors recommend vaccination, but the data that are an essential part of a risk-benefit analysis are omitted.
Both diagnoses U07.1 and U07.2 (without virus detection) were considered inclusion diagnoses. It is essential to break down these two diagnoses, since the PCC construct lacks clarity and is highly psychologically superimposed (12,13) and proper diagnostic evidence is required to avoid information bias (2). Sensitivity analyses should be carried out with just U07.1 as inclusion diagnosis. The authors also admit that: "…symptoms of PCC are frequently observed not only in patients with confirmed covid-19 but also in those without a positive SARS-CoV-2 PCR test result." (p.8) How is this explained when the SARS-CoV-2 PCR test is considered to be the "gold standard"?
Another major concern is the non-blinded diagnosis of PCC, as the authors state that vaccinated individuals might have received a PCC diagnosis less frequently than unvaccinated individuals “owing to expectations from both patients and healthcare providers about the protective effect of vaccination” (p.8).
The proportion of PCC among unvaccinated people with psychiatric comorbidity is three times higher than among vaccinated people with psychiatric comorbidity (2.1% versus 0.7%). On the other hand, somatic comorbidity was higher in the group of the vaccinated than unvaccinated. This is hardly plausible. An analysis of German health insurance data reveals a higher probability of post-COVID-19 in patients with somatic and mental pre-existing conditions (13). Remember that all symptoms described for PCC (14) can also be present in nearly all chronic somatic diseases. The corresponding German agency, the Robert Koch Institute, specifically states that the symptoms should be conceived of as PCC “when they cannot be explained in another way” (15) . If the doctors follow this approach, then somatic comorbidity would “automatically” reduce the diagnostics of PCC because the same symptoms can more easily be explained ”in another way”. The most plausible interpretation of the results is, therefore, that the presence of somatic comorbidity puts down the PCC diagnosis among the vaccinated while psychiatric comorbidity enhances this diagnosis among the unvaccinated.
This means that any comparison of patient groups that significantly differ in somatic and psychiatric comorbidity is strongly biased. These biases do not warrant the authors’ conclusion of "a strong association between covid-19 vaccination before infection and reduced risk of receiving a diagnosis of PCC“.
Oliver Hirsch
Professor of Business Psychology
FOM University of Applied Sciences, Siegen, Germany
Boris Kotchoubey
Professor of Medical Psychology
University of Tübingen, Germany
1 Lundberg-Morris, L., Leach, S., Xu, Y., Martikainen, J., Santosa, A., Gisslén, M., Li, H., Nyberg, F., Bygdell, M. (2023). Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. BMJ. Nov 22;383:e076990. doi: 10.1136/bmj-2023-076990.
2 Høeg, T.B., Ladhani, S., Prasad, V. (2023). How methodological pitfalls have created widespread misunderstanding about long COVID. BMJ Evidence-Based Medicine. Published Online First: 25 September 2023. doi: 10.1136/bmjebm-2023-112338.
3 Brown, R. B. (2021). Outcome Reporting Bias in COVID-19 mRNA Vaccine Clinical Trials. Medicina (Kaunas, Lithuania), 57(3). https://doi.org/10.3390/medicina57030199
4 Olliaro, P., Torreele, E., & Vaillant, M. (2021). COVID-19 vaccine efficacy and effectiveness—the elephant (not) in the room. The Lancet Microbe, 383, 2603. https://doi.org/10.1016/S2666-5247(21)00069-0
5 Alsulamy, N., Lee, A., Thokala, P., & Alessa, T. (2020). What Influences the Implementation of Shared Decision Making: An Umbrella Review. Patient Education and Counseling, Aug 11, Online ahead of print. https://doi.org/10.1016/j.pec.2020.08.009
6 Bobbio M, et al. (1994). Completeness of reporting trial results: Effect on physicians’ willingness to prescribe. Lancet, 343, 1209-1211.
7 Cranney M, Walley T. (1996). Same information, different decisions: The influence of evidence on the management of hypertension in the elderly. British Journal of General Practice, 46, 661-663.
8 McGettigan P, et al. (1999). The effects of information framing on the practices of physicians. Journal of General Internal Medicine 14, 633-642.
9 Austin, P.C. (2010). Absolute risk reductions and numbers needed to treat can be obtained from adjusted survival models for time-to-event outcomes. Journal of Clinical Epidemiology, 63, 46-55.
10 Fagerlin, A., & Peters, E. (2011). Quantitative Information. In B. Fischhoff, N. T. Brewer, & J. S. Downs (Eds.), Communicating Risks and Benefits: An Evidence-Based User´s Guide (pp. 53–64). US Department of Health and Human Services.
11 Ranganathan, P., Pramesh, C. S., & Aggarwal, R. (2016). Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat. Perspectives in Clinical Research, 7(1), 51–53. https://doi.org/10.4103/2229-3485.173773
12 Fleischer, M., Szepanowski, F., Tovar, M., Herchert, K., Dinse, H., Schweda, A., Mausberg, A. K., Holle-Lee, D., Köhrmann, M., Stögbauer, J., Jokisch, D., Jokisch, M., Deuschl, C., Skoda, E.-M., Teufel, M., Stettner, M., & Kleinschnitz, C. (2022). Post-COVID-19 Syndrome is Rarely Associated with Damage of the Nervous System: Findings from a Prospective Observational Cohort Study in 171 Patients. Neurology and Therapy. Advance online publication. https://doi.org/10.1007/s40120-022-00395-z
13 Schulz, M., Mangiapane, S., Scherer, M., Karagiannidis, C., & Czihal, T. (2022). Post-Acute Sequelae of SARS-CoV-2 Infection. Deutsches Ärzteblatt International, 119(10), 177–178. https://doi.org/10.3238/arztebl.m2022.0134
14 National Institute for Health and Care Excellence, Scottish Intercollegiate Guidelines Network and Royal College of General Practitioners (2022). COVID-19 rapid guideline: managing the long-term effects of COVID-19. https://www.nice.org.uk/guidance/ng188
15 RKI (Robert Koch Institute) (2023). Was ist Long Covid? https://www.rki.de/SharedDocs/FAQ/NCOV2019/FAQ_Long-COVID_Definition.html
Competing interests: No competing interests
Dear Editor,
The authors found a strong association between covid-19 vaccination before infection and reduced risk of post-covid-19 condition (PCC) among 589 722 individuals in Sweden.[1]
As noted in the Introduction, general descriptive symptoms of PCC include fatigue, dyspnea, cognitive impairment, headache, muscle pain, and cardiac abnormalities such as chest pain and palpitations. [2] Therefore, these symptoms are very similar to those of some comorbidities, such as cardiovascular disease, respiratory disease, psychiatric disease, etc, which means that the diagnosis of PCC is mainly symptom-based and needs to be diagnosed in the exclusion of other comorbidities. In this study, the vast majority of PCCs were diagnosed in patients with comorbidities (1228 PCCs were diagnosed in vaccinated before covid-19 group in patients with comorbidities, even more than 1201; 3876 PCCs were diagnosed in not vaccinated before covid-19 group in patients with comorbidities) (see Table S4 for details), suggesting that comorbidities are important interference factors in the diagnosis of PCC. Therefore, a detailed analysis of the interference of comorbidities in the diagnosis of PCC is required. In addition, this study included a large number of patients with psychiatric disease (N=168,648), who were more likely to have a range of PCC-like symptoms due to psychiatric factors. Therefore, in order to reach a more convincing conclusion, these factors need to be taken into account.
Shuanggang Chen, M.D.
Department of Oncology, Yuebei People's Hospital, Shantou University Medical College
Shaoguan, China
strugglingchen@126.com
[1] Lundberg-Morris L, Leach S, Xu Y, Martikainen J, Santosa A, Gisslén M, Li H, Nyberg F, Bygdell M. Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. BMJ. 2023 Nov 22;383:e076990. doi: 10.1136/bmj-2023-076990. PMID: 37993131
[2] Crook H, Raza S, Nowell J, Young M, Edison P. Long covid-mechanisms, risk factors, and management. BMJ2021;374:n1648. doi:10.1136/bmj.n1648. pmid:34312178
Competing interests: No competing interests
Dear Editor,
As a response to the Lundberg-Morris et al. 1 study being challenged on the issue that more vaccinated died during the study period than unvaccinated 2, Nyberg and Bygdell 3 defended by saying that “this direct comparison of crude mortality proportions is not justified and will be misleading without adequate adjustments for other factors, including age and comorbidities.” Possibly, but Lundberg-Morris et al. showed that vaccinated had a higher probability of post covid infection, or long covid, in the partially and fully adjusted models than in the crude model (Table 2). Accordingly, I do not find it unlikely that vaccinated would also have a higher probability of mortality in adjusted models than in the crude model.
References
1. Lundberg-Morris L, Leach S, Xu Y, et al. Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. BMJ 2023;383:e076990. doi: 10.1136/bmj-2023-076990
2. Lacout A, Azalbert X, Lesgards J-F, et al. Concern about Covid-19 vaccine efficiency related to biased analyses not captured by the review process Re: Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. Rapid Response BMJ 2023 doi: https://www.bmj.com/content/383/bmj-2023-076990/rr-0
3. Nyberg F, Bygdell M. Re: Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study - Reply by the authors to Lacout et al rapide response. Rapid Response BMJ 2023 doi: https://www.bmj.com/content/383/bmj-2023-076990/rr-2
Competing interests: No competing interests
Dear Editor
The aim of our study was to evaluate the potential vaccine effectiveness against receiving a diagnosis of post-covid-19 condition. Thus, the objective and design of the analyses in this paper was not to investigate acute deaths after infection, nor vaccine-related mortality based on Swedish register data. In fact, we and others have published such analyses that show a strong protective effect of covid vaccines on severe covid-19 disease and death in Sweden and other regions (1-4). The two mortality proportions from our paper calculated by Lacout et al are also easily explained simply by the higher age distribution and frequency of comorbidities in the vaccinated cohort. Thus, this direct comparison of crude mortality proportions is not justified and will be misleading without adequate adjustments for other factors, including age and comorbidities.
Secondly, we have indeed adjusted the analyses for the variant at time of primary infection in the main analysis, which essentially ensures that these comparisons are made within strata of predominant variant, and the result then becomes a summary across these comparisons. We have also presented analyses stratified for predominant variant, which showed limited variation, with somewhat higher vaccine protection during the delta-dominant period (Suppl Table S4).
Lastly, all included individuals in our study have had an infection and the risk of infection is not studied, nor presented, in our study. Since we have performed both virus variant adjustment stratification, as well as stratified analyses by dose which compares unvaccinated and vaccinated with the same number of doses, the proposed issue of different baseline rates of infection is not relevant.
Thus, we do not agree with the points raised by Latour et al and we stand by our results.
On behalf of all authors,
Fredrik Nyberg and Maria Bygdell
References
1. Nordström P, Ballin M, Nordström A. Risk of infection, hospitalisation, and death up to 9 months after a second dose of COVID-19 vaccine: a retrospective, total population cohort study in Sweden. Lancet. 2022 Feb 26;399(10327):814–23.
2. Katikireddi SV, Cerqueira-Silva T, Vasileiou E et al. Two-dose ChAdOx1 nCoV-19 vaccine protection against COVID-19 hospital admissions and deaths over time: a retrospective, population-based cohort study in Scotland and Brazil Lancet. 2022 Jan 1;399(10319):25-35
3. Wu, N, Joyal-Desmarais K, Ribeiroet PAB et al. Long-term effectiveness of COVID-19 vaccines against infections, hospitalisations, and mortality in adults: findings from a rapid living systematic evidence synthesis and meta-analysis up to December, 2022. The Lancet Respiratory Medicine 11.5 (2023): 439-452.
4. Xu Y, Li H, Kirui B et al. Effectiveness of COVID-19 Vaccines over 13 Months Covering the Period of the Emergence of the Omicron Variant in the Swedish Population. Vaccines (Basel) 2022 Vol. 10 Issue 12
Competing interests: FN owns some AstraZeneca shares.
Dear Editor,
The Lundberg-Morris et al. [1] study showing that more unvaccinated than vaccinated had post-covid-19 condition, or post covid, also shows that more vaccinated than unvaccinated died during the study period [2]. The diverging results are puzzling but may be due to strong imbalances in the study groups, which I elaborate on here.
21.8 times more unvaccinated were infected early when pre-Alpha- or Alpha variants dominated than vaccinated, and 6.0 times more vaccinated than unvaccinated were infected late when Omicron variants dominated. In parallel, 2.5 times more unvaccinated were hospitalized, and 5.2 times more were under intensive care than vaccinated (discussing reasons for this belongs elsewhere). The numbers inform that the groups are very different along at least two important dimensions where unvaccinated were predominately infected by pre-Alpha- or Alpha variants and had high morbidity, and vaccinated were predominately infected by Omicron variants and had low morbidity.
The study controls for the above and other issues. Still, it does not consider that the groups have relatively few overlapping data points along different dimensions, inducing extrapolation bias, according to King and Zeng [3]. As a remedy, they recommend matching, pruning – with the risk of data loss, and balancing, but Lundberg-Morris et al. did not do that.
However, they did analyze different strata separately without necessarily solving the problem of extrapolation bias. For instance, they found in the stratum not hospitalized that unvaccinated were more exposed to long covid than the vaccinated, in line with the study’s major conclusion. Still, the study compared the unvaccinated with the vaccinated stratum where the first group was predominately infected when pre-Alpha- Alpha variants dominated, and the last when Omicron variants dominated. According to the above discussion, comparing such different groups can induce bias, even with relevant controls.
It speaks to the study’s advantage that long covid was relatively widespread among the unvaccinated, regardless of the dominant variant. Still, since the group had a progressively higher proportion of people hospitalized and under intensive care than vaccinated, it is reasonable to assume that morbidity was also relatively high among the unvaccinated in the stratum not hospitalized. Consequently, this may have explained long covid as much as vaccination status.
References
1. Lundberg-Morris L, Leach S, Xu Y, et al. Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. BMJ 2023;383:e076990. doi: 10.1136/bmj-2023-076990
2. Lacout A, Azalbert X, Lesgards J-F, et al. Concern about Covid-19 vaccine efficiency related to biased analyses not captured by the review process Re: Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. Rapid Response BMJ 2023 doi: https://www.bmj.com/content/383/bmj-2023-076990/rr-0
3. King G, Zeng L. The Dangers of Extreme Counterfactuals. Political Analysis 2006;14(2):131-59.
Competing interests: No competing interests
Dear Editor
Lundberg-Morris et.al. (1) sought to determine “the importance of primary vaccination against covid-19 to reduce the population burden of post-covid condition (PCC).” Among persons who had been diagnosed with covid-19, they observed a 21% - 73% reduction in PCC incidence associated with receipt of covid-19 vaccine prior to their illness, the size of the reduction depending on the number of vaccinations. However, covid-19 vaccination also substantially reduces the risk of developing covid-19 infection itself, and this is another basis for vaccination having an impact on PCC incidence. Therefore, the “importance” of covid-19 vaccination in the population at large must be substantially greater than that suggested by the results obtained in this population of covid-19 patients.
Reference
1. Lundberg-Morris L, Leach S, Xu Y, et. al. Covid-19 vaccine effectiveness against post-covid condition among 589,722 individuals in Sweden: population based cohort study. BMJ 2023;383:e076990 http://dx.doi.org/10.1136/bmj-2023-076990
Competing interests: No competing interests
Dear Editor,
We read with interest the paper by Lisa Lundberg-Morris, et al. (1) which reviewed the Covid-19 vaccine effectiveness against post-covid-19 condition in a population-based cohort in Sweden of 589 722 individuals. It raises a number of significant concerns in the analyses conducted and its conclusions. This paper analyses two cohorts. Cohort A: not vaccinated prior to having Covid-19; cohort B: vaccinated prior to having Covid-19.
The first observation relates to the death ratio in cohort A (0.28%, 821/290030) which is significantly lower (p=0.001) than in cohort B (0.36%, 1076/299692). The risk of death is in fact the most important, while the other items can be qualified as intermediate criteria.
In addition, neutralizing and facilitating antibodies may be produced against the virus. The modeling work published by Yahi et al. shows that antibodies facilitating the spread of the virus (ADE) have more affinity with the spike protein than neutralizing antibodies in regard to the delta variant (on the contrary to what is observed with the original strain of SARS-CoV-2 of 2020, Wuhan/D614G) (2). The appearance of a given variant may thus favour the ADE phenomenon, and could explain why the vaccine (developed from the first strain of the virus) can be deleterious in certain cases. As a matter of fact, 59 349 individuals were excluded from the analysis because events occurred less than 28 days of Covid-19 index date (56 760 vaccinated, 2515 died, 74 emigrated). The reason for exclusion was vaccination for 56 760 patients and death for 2515. The cause of death is unknown and should have been analysed. We do not know how many of these patients were vaccinated. This intermediate group should have been analysed to model the trend or adapt the less than 28 days of covid-19 index date exclusion.
The third observation is related to a cohort bias as cohort A has been exposed to different variants compared to cohort B. 60.2% of persons in cohort A had a variant Alpha predominant during acute infection versus 3.5% in cohort B. And cohort B had variant Omicron predominant at 74.9% vs 12.4% for cohort A.
Populations are heterogenous and cannot be compared as they are not exposed to the same variants, each of which has a different morbidity and lethality. Indeed, Liu Y et al. reported that infection fatality ratio of Omicron variant was reduced by 78.7% (95% confidence interval: 66.9%, 85.0%) with respect to previous variants (3). In Lisa Lundberg-Morris, et al.’s study, the vaccinated population (Cohort B) was predominantly exposed to much more benign variants than the unvaccinated population (Cohort A).
Vaccination effectiveness against post covid-19 condition should thus have been done by variant to cope for the different fatality ratio by variant. This bias, which is of crucial importance, is not mentioned in the limitation of the study.
Last but not least, the risk of infection was higher with the higher number of vaccine doses, which should have been discussed (4). Variant matching is essential to draw a reliable conclusion about vaccine efficacy.
Altogether, we raise serious concerns about the analytical choices made for the study, its conclusions and the review process which should have caught these significant issues. Furthermore, this study should raise the significant ethical concern for the scientific community on the scientific analytical integrity matters.
The conclusions of such a study may impact significantly public policies and have critical consequences for the health of populations exposed to the virus and for whom the vaccine is proposed. The data set should also be publicly communicated for further independent external analysis.
REFERENCES
1. Lundberg-Morris L, Leach S, Xu Y, Martikainen J, Santosa A, Gisslén M, Li H, Nyberg F, Bygdell M. Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study. BMJ. 2023 Nov 22;383:e076990. doi: 10.1136/bmj-2023-076990. PMID: 37993131; PMCID: PMC10666099.
2. Yahi N, Chahinian H, Fantini J. Infection-enhancing anti-SARS-CoV-2 antibodies recognize both the original Wuhan/D614G strain and Delta variants. A potential risk for mass vaccination. J Infect 83 (2021): 607-635.
3. Liu Y, Yu Y, Zhao Y, He D. Reduction in the infection fatality rate of Omicron variant compared with previous variants in South Africa. Int J Infect Dis. 2022 Jul;120:146-149. doi: 10.1016/j.ijid.2022.04.029. Epub 2022 Apr 21. PMID: 35462038; PMCID: PMC9022446.
4. Shrestha NK, Burke PC, Nowacki AS, Simon JF, Hagen A, Gordon SM. Effectiveness of the Coronavirus Disease 2019 Bivalent Vaccine. Open Forum Infect Dis. 2023 Apr 19;10(6):ofad209. doi: 10.1093/ofid/ofad209. PMID: 37274183; PMCID: PMC10234376.
Competing interests: No competing interests
Re: Covid-19 vaccine effectiveness against post-covid-19 condition among 589 722 individuals in Sweden: population based cohort study - Reply by the authors to rapid responses
Dear Editor
We would like to address additional comments made in rapid responses to our article.
Prof Aarstad raised concerns about potential insufficient overlap due to differences between groups and time periods. A major strength of our study lies in the large sample size, even within different strata, which serves to mitigate this concern. As he also acknowledges, we have adjusted for such differences in several ways, and present stratified analyses that reduce differences by restricting to certain subgroups or time periods. Our diverse analyses consistently indicated no need for further matching, pruning, or balancing.
Addressing Prof Aarstad’s speculations regarding deaths listed in Table S2, we emphasize our study was not designed to evaluate death as an outcome. Furthermore, these deaths do not represent mortality in the two groups but only describes one of several alternative first reasons for censoring (terminating follow-up) in our study. To reliably investigate death as an outcome, another study design is required.
Regarding comments by S Chen, and Prof Hirsch and Prof Kotchoubey, regarding the symptomatology and diagnosis of PCC, we acknowledge that symptom patterns overlap with many other diseases, a common feature among medical conditions generally. Physicians are well familiar with this, and assessing differential diagnoses and ruling out alternative diagnoses are a routine part of their work, and the reality that diagnoses are not assigned blinded to medical history is an integral part of healthcare. We relied on PCC diagnoses by physicians from the healthcare system, so that PCC would be the physician assessment of the most likely diagnosis in an individual. In addition, we both adjusted and stratified for comorbidities, with consistent results.
Both Chen and Hirsch/Kotchoubey also seem to misinterpret Table S4. The comorbidity groups are not mutually exclusive, so the same patient could have e.g. respiratory and cardiovascular disease, and the numbers cannot be added. Further, there is a higher PCC frequency among both individuals with psychiatric and somatic diseases (0.6%-0.8% in vaccinated and 2.1%-3.5% in unvaccinated) compared with the overall (0.4% in vaccinated and 1.4% in unvaccinated), which aligns with the German source cited.
Concerning Hirsch and Kotchoubey’s query about relative or absolute effects, we would argue that both have their uses and can be interpreted and understood. We would also hesitate to call the difference they refer to (1.4%-0.4%) a risk reduction of “only” 1%, as 1% of almost 600,000 individuals (as our study population) represents around 6000 individuals who would have been protected from PCC.
Our study was designed to evaluate PCC as an outcome, therefore, the follow-up started at 28 days after index date since individuals were not at risk for PCC before 28 days. Again, a different study design is required to evaluate individuals not included in this study and the numbers provided in this study cannot be used for ad hoc speculative crude analyses for other purposes.
Regarding the use of diagnoses U07.1/U07.2 vs. PCR test, we acknowledge that PCR testing is indeed a gold standard for specificity and quite sensitive when available and used, but the diagnosis without available test result (U07.2) is assigned with strong reason, and in this situation is likely to also have a reasonably high validity. Importantly, the vast majority (>90%) of our study population did have a positive PCR-test registered.
Finally, although our study does not address the total risk-benefit balance of vaccination against Covid-19, we agree with Emeritus Prof Weiss’ comment that the benefits of vaccination go beyond the direct benefit of PCC risk reduction.
In conclusion, we stand by our results, and also note recent evidence using alternative data and methods that provide highly consistent results (1).
On behalf of all authors,
Fredrik Nyberg and Maria Bygdell
References:
1. Català M, Mercadé-Besora N, Kolde R, Trinh NTH, Roel E, Burn E, Rathod-Mistry T, Kostka K, Man WY, Delmestri A, Nordeng HME, Uusküla A, Duarte-Salles T, Prieto-Alhambra D, Jödicke AM. The effectiveness of COVID-19 vaccines to prevent long COVID symptoms: staggered cohort study of data from the UK, Spain, and Estonia. Lancet Respir Med. 2024 Jan 11:S2213-2600(23)00414-9. doi: 10.1016/S2213-2600(23)00414-9. Epub ahead of print. PMID: 38219763.
Competing interests: FN owns some AstraZeneca shares.